/** Author: Philip Abbet (philip.abbet@idiap.ch)

    Simple example of a heuristic: Identity. The features are a copy of the
    (grayscale) pixels contained in the processed region of interest.
*/

#include <mash/heuristic.h>

using namespace Mash;


//------------------------------------------------------------------------------
/// The 'Identity' heuristic class
//------------------------------------------------------------------------------
class IdentityHeuristic: public Heuristic
{
    //_____ Construction / Destruction __________
public:
    IdentityHeuristic();
    virtual ~IdentityHeuristic();


    //_____ Implementation of Heuristic __________
public:
    virtual unsigned int dim();

    virtual scalar_t computeFeature(unsigned int feature_index);
};


//------------------------------------------------------------------------------
/// Creation function of the heuristic
//------------------------------------------------------------------------------
extern "C" Heuristic* new_heuristic()
{
    return new IdentityHeuristic();
}



/************************* CONSTRUCTION / DESTRUCTION *************************/

IdentityHeuristic::IdentityHeuristic()
{
}


IdentityHeuristic::~IdentityHeuristic()
{
}


/************************* IMPLEMENTATION OF Heuristic ************************/

unsigned int IdentityHeuristic::dim()
{
    // We have has many features than pixels in the region of interest
    unsigned int roi_size = roi_extent * 2 + 1;
    return roi_size * roi_size;
}


scalar_t IdentityHeuristic::computeFeature(unsigned int feature_index)
{
    // Compute the coordinates of the top-left pixel of the region of interest
    unsigned int x0 = coordinates.x - roi_extent;
    unsigned int y0 = coordinates.y - roi_extent;

    // Compute the coordinates of the pixel corresponding to the feature, in
    // the region of interest
    unsigned int roi_size = roi_extent * 2 + 1;
    unsigned int x = feature_index % roi_size;
    unsigned int y = (feature_index - x) / roi_size;

    // Return the pixel value corresponding to the desired feature
    byte_t** pLines = image->grayLines();
    return (scalar_t) pLines[y0 + y][x0 + x];
}